water-07-06056.pdf

Natural Hazards, 2014

This study proposes a risk assessment framework for quantifying the reliability of the rainfall threshold used in flash flood warning, which should be influenced by the uncertainties in the rainfall characteristics, including rainfall duration, depth, and storm pattern. This risk assessment framework incorporates the correlated multivariate Monte Carlo simulation method, the Sobek 1D-2D hydrodynamic model, and a logistic regression equation to establish a quantile relationship of the rainfall threshold for quantifying reliability of the rainfall threshold. The Shuhu Creek catchment locates in East Taiwan, and its historical hourly rainfall records on eight typhoon events are used as the study area and data. The results from the proposed framework indicate that the variation in the rainfall threshold declines with the duration; 12-h duration associated with a stable coefficient of variance of the rainfall threshold appears to be appropriate for the flash flood warning in the Shuhu Creek catchment. Moreover, the issued rainfall thresholds in the Shuhu Creek catchment by Water Resources Agency in Taiwan have a low exceedance probability. This infers that inundation might occur as the observed rainfall depth approaches the threshold, so that it is necessary to lower the rainfall threshold in accordance with higher exceedance probability in order to achieve the goal of early flood warning.

Stochastic Environmental Research and Risk Assessment, 2021

This study proposed an equation for Rainfall Threshold for Flood Warning (RTFW) for small urban watersheds based on computer simulations. First, a coupled 1D-2D dual-drainage model was developed for nine watersheds in Seoul, Korea. Next, the model simulation was repeated for a total of 540 combinations of the synthetic rainfall events and watershed imperviousness (9 watersheds x 4 NRCS Curve Number (CN) values x 15 rainfall events). Then, the results of the 101 simulations that caused the critical flooded depth (0.25m-0.35m) were used to develop the equation that relates the value of RTFW to the rainfall event temporal variability (represented as coefficient of variation or CV) and the watershed Curve Number. The results suggest that (1) RTFW exponentially decreases as the rainfall CV increases; (2) RTFW linearly decreases as the watershed CV increases; and that (3) RTFW is dominated by CV when the rainfall has low temporal variability (e.g., CV<0.2) while RTFW is dominated by CN when the rainfall has high temporal variability (e.g., CV>0.4). For validation, the proposed equation was applied for the flood warning system with two storm events occurred in 2010 and 2011 over 239 watersheds in Seoul. The system showed the the hit, false and missed alarm rates at 69% (48%), 31% (52%) and 6.7% (4.5%), respectively for the 2010 (2011) event.

Water

Increasingly frequent, high-intensity rain events associated with climatic change are driving urban drainage systems to function beyond their design discharge capacity. It has become an urgent issue to mitigate the water resource management challenge. To address this problem, a real-time procedure for predicting the inundation risk in an urban drainage system was developed. The real-time procedure consists of three components: (i) the acquisition and forecast of rainfall data; (ii) rainfall-runoff modeling; and (iii) flood inundation mapping. This real-time procedure was applied to a drainage system in the Sukhumvit area of Bangkok, Thailand, to evaluate its prediction efficacy. The results showed precisely that the present real-time procedure had high predictability in terms of both the water level and flood inundation area mapping. It could also determine hazardous areas with a certain amount of lead time in the drainage system of the Sukhumvit area within an hour of rainfall data...

Natural Hazards

This paper presents an improved method of using threshold of peak rainfall intensity for robust flood/flash flood evaluation and warnings in the state of São Paulo, Brazil. The improvements involve the use of two tolerance levels and the delineating of an intermediate threshold by incorporating an exponential curve that relates rainfall intensity and Antecedent Precipitation Index (API). The application of the tolerance levels presents an average increase of 14% in the Probability of Detection (POD) of flood and flash flood occurrences above the upper threshold. Moreover, a considerable exclusion (63%) of non-occurrences of floods and flash floods in between the two thresholds significantly reduce the number of false alarms. The intermediate threshold using the exponential curves also exhibits improvements for almost all time steps of both hydrological hazards, with the best results found for floods correlating 8-h peak intensity and 8 days API, with POD and Positive Predictive Valu...

Hydrology and Earth System Sciences, 2005

Since medium and long-term precipitation forecasts are still not reliable enough, rough estimates of the degree of the extremity of forthcoming flood events that might occur in the course of dangerous meteorological situations approaching a basin could be useful to decision-makers as additional information for flood warnings. One approach to answering such a problem is to use real-time data on the soil moisture conditions in a catchment in conjunction with estimates of the extremity of the future rainfall and experience with the basins behaviour during historical floods. A scenario-based method is proposed for such a future flood risk estimation, based on an a priori evaluation of the extremity of hypothetical floods generated by combinations of synthetic extreme precipitation and previously observed antecedent pre-flood basin saturations. The Hron river basin, located in central Slovakia, was chosen as the pilot basin in the case study. A time series of the basins average daily precipitation was derived using spatial interpolation techniques. A lumped HBV-type daily conceptual rainfallrunoff model was adopted for modelling runoff. Analysis of the relationship of the modelled historical pre-flood soil moisture and flood causing-precipitation revealed the independence of both quantities for rainfall durations lasting 1 to 5 days. The basins average annual maximum 1 to 5 day precipitation depths were analysed statistically and synthetic extreme precipitation scenarios associated with rainfall depths with return periods of 5, 20, 50 and 100 years, durations of 1 to 5 days and temporal distribution of extreme rainfall observed in the past were set up for runoff simulation. Using event-based flood simulations, synthetic flood waves were generated for random combinations of the rainfall scenarios and historical pre-flood soil moisture conditions. The effect of any antecedent basin saturation on the extremity of floods was quantified empirically and critical values of the basin saturation leading to floods with a higher return period than the return period of precipitation were identified. A method for implementing such critical values into flood risk warnings in a hydrological forecasting and warning system in the basin was suggested.

Mathematical Modelling in Civil Engineering, 2016

Flash floods are highly variable phenomena in both time and space. Therefore, tools with the potential to provide early warning are needed to analyse them. In Europe, flash floods often occur on small catchments; it has already been shown that the spatial variability of rainfall has a great impact on the catchment response. The aim of this paper is to use a coupled hydrological-hydraulic model (MIKE SHE/MIKE 11) to determine the rainfall thresholds and transformation coefficients from hourly rain to other durations, which will lead to flooding of the inhabited areas to the ungauged Ungureni catchment. The model was calibrated and validated using a reference discharge previously obtained by UTCB at the downstream gauge section of Teleorman River (Tatarastii de Sus) using MIKE 11 UHM module. Once the rainfall thresholds are determined, they can be used in flood forecasting and issuing warning with lead time for the inhabitants of the two villages located in Ungureni watershed. The met...

Journal of Flood Risk Management, 2021

Rapidly expanding cities in the Middle Eastern and North African (MENA) region are at risk of flooding due to heavy rainfall, insufficient drainage capacity, a lack of preparedness and insufficient data to conduct required studies. A low regret Early Warning Systems (EWS) using rainfall thresholds is proposed as a cost-effective short-term solution. This study aims to utilise a probabilistic approach to characterise and predict urban floods by assessing critical rainfall thresholds likely to cause flooding combined with ensemble precipitation forecast in Alexandria, Egypt. Rainfall thresholds were inferred by associating observed rainfall and historical flood information sourced from social media and newspapers. Floods were classified in a colour-coded hazard matrix as no flood (green), minor flood (yellow), significant flood (orange), and severe flood (red). Probability of occurrence of hazard classes was derived by incorporating ensemble rainfall into the hazard matrix to jointly evaluate likelihood and hazard severity. Results from this study showed that three of four severe events analysed could have been predicted with a high likelihood up to 24 hr before. The presented approach supports decision making to issue warnings and flood control actions with limited data and is a model for other data scare regions.

Water

This paper aims to demonstrate the research-to-application and operational use of numerical hydrologic and hydraulic modeling to (a) quantify potential flash flood risks in small urban communities with high spatial resolution; (b) assess the effectiveness of possible flood mitigation measures appropriate for such communities; and (c) construct an effective operational urban flash flood warning system. The analysis is exemplified through case studies pertaining to a small community with dense housing and steep terrain in Tegucigalpa, Honduras, through numerical simulations with a customized self-contained hydrologic and hydraulic modeling software. Issues associated with limited data and the corresponding modeling are discussed. In order to simulate the extreme scenarios, 24-h design storms with return periods from 1 to 100 years with distinctive temporal and spatial distributions were constructed using both daily and hourly precipitation for each month of the rainy season (May–Octob...

2008

In Mediterranean Europe, flash flooding is one of the most devastating hazards in terms of loss of human life and infrastructures. Over the last two decades, flash floods have caused damage costing a billion Euros in France alone. One of the problems of flash floods is that warning times are very short, leaving typically only a few hours for civil protection services to act. This study investigates if operationally available short-range numerical weather forecasts together with a rainfall-runoff model can be used for early indication of the occurrence of flash floods. One of the challenges in flash flood forecasting is that the watersheds are typically small, and good observational networks of both rainfall and discharge are rare. Therefore, hydrological models are difficult to calibrate and the simulated river discharges cannot always be compared with ground measurements. The lack of observations in most flash flood prone basins, therefore, necessitates the development of a method where the excess of the simulated discharge above a critical threshold can provide the forecaster with an indication of potential flood hazard in the area, with lead times of the order of weather forecasts. This report is focused on four case studies in Mediterranean part of Europe: i) The September 2002-flash flood event in the Cévennes-Vivarais region in the Southeast of the Massif Central in France, a region known for devastating flash flood; ii) the August 2003-flash flood event in both Fella subcatchment of Tagliamento watershed and upstream part of Isonzo river basin, iii) the October 2006-flash flood event in Isonzo river basin and iv) the September 2007-flash flood event in Upper Sava river basin in Slovenia. The French case study is described in more detail with the principles and metholodigies being explained that are then applied to the remaining three case studies. Also, there were more data available for the 1 st case study. The critical aspects of using numerical weather forecasting for flash flood forecasting are being described together with the threshold-exceedance approach previously postulated for the European Flood Alert System (EFAS). The short-range weather forecasts, from the Local model of the German national weather service, are driving the LISFLOOD model, a hybrid between conceptual and physically based rainfall-runoff model. Results of the study indicate that high resolution operational weather forecasting combined with a rainfall-runoff model could be useful to determine flash floods more than 24 hours in advance.

Water, 2019

Owing to their short duration and high intensity, flash floods are among the most devastating natural disasters in metropolises. The existing warning tools-flood potential maps and two-dimensional numerical models-are disadvantaged by time-consuming computation and complex model calibration. This study develops a data-driven, probabilistic rainfall-inundation model for flash-flood warnings. Applying a modified support vector machine (SVM) to limited flood information, the model provides probabilistic outputs, which are superior to the Boolean functions of the traditional rainfall-flood threshold method. The probabilistic SVM-based model is based on a data preprocessing framework that identifies the expected durations of hazardous rainfalls via rainfall pattern analysis, ensuring satisfactory training data, and optimal rainfall thresholds for validating the input/output data. The proposed model was implemented in 12 flash-flooded districts of the Xindian River. It was found that (1) hydrological rainfall pattern analysis improves the hazardous event identification (used for configuring the input layer of the SVM); (2) brief hazardous events are more critical than longer-lasting events; and (3) the SVM model exports the probability of flash flooding 1 to 3 h in advance.